In this thesis, we examine a recent paradigm for solving dynamic optimization problems under uncertainty, whereby one considers decisions that depend directly on the sequence of observed disturbances. The resulting policies, ...

We propose new models and optimization methods for airline revenue management and pricing. In the first part of this thesis, we study the dynamic inventory control problem for a single flight under imperfect market ...

The electricity industry has been experiencing fundamental changes over the past decade. Two of the arguably most significant driving forces are the integration of renewable energy resources into the electric power system ...

Optimization in the presence of uncertainty is at the heart of operations research. There are many approaches to modeling the nature of this uncertainty, but this thesis focuses on developing new algorithms, software, and ...

This thesis investigates the Aircraft Sequencing Problem (ASP) with Arrivals and Departures. The ASP is the problem of sequencing the arriving and departing aircraft on a single nmway to minimize certain performance criteria. ...

The cost of air traffic delays is well documented, and furthermore, it is known that the significant proportion of delays is incurred at airports. Much of the air traffic flow management literature focuses on traffic flows ...

(cont.) Second, for almost all 0-1 bipartite instances, we give a lower bound on the integrality gap of various linear programming relaxations of this problem. Finally, we show that for almost all 0-1 bipartite instances, ...

(cont.) However, these randomized algorithms can never provide proven upper or lower bounds on the number of objects they are counting, but can only give probabilistic estimates. We propose a set of deterministic algorithms ...

In the first part of this thesis we present a new, geometric interpretation of the jump number problem on 2-dimensional 2-colorable (2D2C) partial order. We show that the jump number of a 2D2C poset is equivalent to the ...

This thesis presents efficient algorithms that give optimal or near-optimal solutions for problems with non-linear objective functions that arise in discrete, continuous and robust optimization. First, we present a general ...

This thesis describes several directions to replace the gradient in James Schor's gradient algorithm to solve the dual problem. The alternative directions are: the variance and standard deviation of buffer levels, the ...

We develop a simulation model based on patient data from 2/1/05 to 1/31/06 that represents the operations of the Emergency Department at Beth Israel Deaconess Medical Center, a Harvard teaching hospital and a leading medical ...

In this thesis, we investigate the batch sizing problem for a custom-job production facility. More specifically, given a production system that has been assigned several different types of custom jobs, we try to derive ...

In this thesis we study three problems related to financial modeling. First, we study the problem of pricing Employee Stock Options (ESOs) from the point of view of the issuing company. Since an employee cannot trade or ...

Since chemotherapy began as a treatment for cancer in the 1940s, cancer drug development has become a multi-billion dollar industry. Combination chemotherapy remains the leading treatment for advanced cancers, and cancer ...

Hypertension is a major public health issue worldwide, affecting more than a third of the adult population and increasing the risk of myocardial infarction, heart failure, stroke, and kidney disease. Current clinical ...

Financing drug development has a particular set of challenges including long development times, high chance of failure, significant market valuation uncertainty, and high costs of development. The earliest stages of ...

Cancer is a leading cause of death both in the United States and worldwide. In this thesis we use machine learning and optimization to identify effective treatments for advanced cancers and to identify effective screening ...